5 Important HR Technology Trends and Topics

This fall at the
HR Technology Conference in Las Vegas, two HR Technology thought leaders, Jason Averbrook, CEO,
Knowledge Infusion and Naomi Bloom, Managing Partner, Bloom & Wallace will square off about the biggest issues faced by HR technology practitioners today. In this entry, I address the same topics that will be discussed at the debate through the lens of my organization,

SaaS vs On-Premise Software: If SaaS delivery prevails over on-premise software, what should practitioners be thinking about their last generation installed systems?

My take:

There is little doubt. SaaS delivery will prevail over time, sooner rather than later.

During this transition, however, newer SaaS technologies can often easily add value (and data) to existing systems. For example, existing talent management or business intelligence systems can extend their life by combining and correlating new data types i.e. data about the people executing outcomes, with traditional data gathered. Existing systems can be enhanced by outside data types for years, extending the time-to-replacement.

Talent Management: Is Talent Management dying as a separate category?

My take: Yes.

Talent Management software has been an HR tool which keeps most of it’s usefulness in HR. Data housed in Talent Management software provides just part of an answer. It makes little business sense to disconnect this data and this system from all other business intelligence. Doing so minimizes it’s value as compared to data gathered from the rest of the business.

Current Talent Management solutions essentially report on history or “what has happened” (lower value). Modern Business Intelligence and Analytics efforts have moved beyond reporting to the need to “predict and prevent” (higher value). Talent Management needs to begin providing data that will combine and correlate well with the larger initiative of predicting and preventing. A data element that can combine and correlate with every other piece of data currently collected to forecast outcomes – is data about the people themselves – talent analytics.

Mobile Applications: How should mobile applications be done right?

My Take:

Mobile applications need to accomodate the rapid assembling and disassembling of teams, groups, managers, companies and the resulting collaboration challenges.

As an example: imagine social software helping me locate someone that can help and taking the additional step of providing easily understood guidance about the best approach / how to connect / what to avoid / what the individual or team personally cares about to reduce the amount of communication errors.

Workforce Analytics: What keeps companies from getting started with workforce analytics?

My Take:

We believe there are two reasons:

Current workforce analytics measure data that “reports on history” but it’s still more difficult to use this data to answer questions about future outcomes (like most Business Intelligence initiatives). Until workforce analytics can begin forecasting or answering “why”, ROI for workforce analytics initiatives will have limited value. Talent Analytics’ work shows that forecasting how the people doing the work will respond, also helps to forecast likely business outcomes. This is a major step towards forecasting, predicting and preventing.

Workforce analytics “sound and seem” unappealing to both Finance and HR – so they avoid owning this initiative. HR Professionals have traditionally not loved the analytics side of business and Analytics Professionals have traditionally not loved the people side of business. Workforce analytics as an initiative have had issues with finding an excited owner. Our opinion is that workforce analytics should be owned by those who currently own business intelligence initiatives.

What are your thoughts on these areas? Comment here or via
@talentanalytics on twitter.